Method and device for investigation of phase transformations in metals and alloys

ABSTRACT

A device and method for investigating phase transformation properties and structural changes of materials. In one form, the device simulates actual thermal processing conditions, while the method can be used in both simulations as well as in actual processing conditions. An analysis using at least one of the device and method is referred to as a single sensor differential thermal analysis, as it compares the temperature recorded in a measured specimen against a reference thermal history without requiring the derivation of the reference thermal history from measured reference temperatures.

This application claims the benefit of the filing date of U.S.Provisional Application No. 60/673,879, filed Apr. 22, 2005.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was supported by the government under Contract No.DGE-0312160 awarded by the National Science Foundation (NSF). Thegovernment has certain rights in the invention.

BACKGROUND OF THE INVENTION

The present invention generally relates to a device and method formeasuring the physical property of a material as a function of thatmaterial's temperature, and more particularly to a device and method formeasurement of solid-liquid and solid-state phase transformations andstructural changes in materials under simulated and actual conditionsassociated with thermal and thermo-mechanical processing of suchmaterials.

The solid-liquid and solid-state phase transformation and structuralchanges that occur in metallic materials during thermal andthermo-mechanical processing determine their final microstructure andhence their mechanical and physical (in-service) properties. These phasetransformations and structural changes are also closely related to thefabricability (weldability, castability, formability or the like) ofconventional and modern structural alloys, and consequently to theirsuccessful implementation as materials for advanced structuralapplications.

Extensive investigations have been performed worldwide, aimed atdeveloping practical methods to measure and subsequently control thephase transformations and structural changes in metallic materials, inorder to improve their fabricability and structural properties.Effective methods for studying of phase transformations and structuralchanges can be used for the development of new materials and advancedprocessing applications.

There are known various techniques and devices for evaluating phasetransformation information in simulated and actual material processingenvironments. Examples of such evaluation include thermal, differentialthermal and dilatometric analyses.

The method for thermal analysis (TA) allows direct determination ofphase transformation temperatures from heating/cooling curves wherelarge thermal effects cause significant change of the heating/coolingrate. This method is mainly applicable in equilibrium conditions and canbe used in simulated, as well as in-situ, conditions. TA can also beapplied during processing when the phase transformations are accompaniedby release of large amounts of heat as in solidification of castings, orlarge weld pools. TA is insensitive to phase transformations andstructural changes with small thermal effects that occur atnon-equilibrium heating and cooling rates, as for example in welding.

Differential thermal analysis (DTA), is used for investigating phasetransformations in materials where a specimen of the investigatedmaterial and a reference specimen experience the same heating andcooling thermal cycle in a controlled environment. In such technique,the material of the reference specimen does not undergo any phasechanges in the investigated temperature range, while that of thespecimen being investigated typically does. The heat consumption orrelease that accompany the phase transformations impact the heating andcooling rates of the investigated specimen. These heat effects arerevealed by plotting the difference in the temperature of the twospecimens versus time or the current temperature. Changes in the samplethat lead to release or absorption of heat can be used in determiningthe phase transformation temperatures of the sample. The method anddevices for DTA have high sensitivity to the thermal effects of phasetransformations and structural changes. The traditional DTA techniqueutilizes sophisticated and expensive devices that operate in a shortrange of heating and cooling rates of up to about twenty degrees Celsiusper minute. Such limitation makes this approach inapplicable forinvestigating the phase transformation in materials where actualprocessing conditions must be simulated. For example, the heating andthe cooling rates of actual processing conditions are normally muchhigher, reaching up to several hundred degrees per second.

Continuous cooling transformation (CCT) diagrams are one of two maintypes of transformation diagrams that are used to optimize a metal'sprocessing path to achieve a given set of properties. CCT diagramsmeasure the extent of phase transformation as a function of time for acontinuously decreasing temperature. This allows the metal to be heatedand then cooled at some rate so that the degree of transformation can bemeasured by dilatometry or other methods. In welding (for example) thesediagrams allow the welding engineer to select the range of coolingrates, and the respective operational window of heat inputs thatprovides the optimal combination of microstructural constituents in theheat affected zone (HAZ) and weld metal. CCT diagrams are typicallyconstructed by simulating weld thermal histories over numerouslaboratory scale specimens. This approach is limited in depicting theactual heating and cooling rates and thermal gradients, and utilizesexpensive, specialized equipment. Such an approach is not applicable forinvestigating solidification and solid-state phase transformations inthe weld metal and therefore is not useful for constructing weld metalCCT diagrams. DTA methods and devices were also used for constructingCCT diagrams; however, because of the maximum heating and cooling ratesfor these techniques are so low, thet are generally inappropriate forconstructing a useful CCT diagram.

Methods for investigating the phase transformations under actual weldingconditions have been conducted, where the temperature changes in aparticular point of a real welded joint during welding were recorded.The method of differentiation of recorded thermal histories can beapplied in-situ by analog or digital differentiation of the weld thermalhistory, in order to reveal the small thermal effects of phasetransformations occurring in the HAZ. Disadvantages of such a methodinclude the amplification of electromagnetic noise, recorded over thethermal cycle, the low sensitivity to and difficult recognition ofhigher temperature phase transformations, and low accuracy ofdetermining phase transformation starting and finishing temperatures.

More recently, the original two-thermocouple version of DTA was appliedduring actual welding and partly solved some of the above mentionedproblems. In such approach the reference thermal cycle is recorded by athermocouple inserted into a tube of austenitic stainless steel, whichdoes not undergo solid-state phase changes. The two thermocouples areequally positioned into the heat affected zone (HAZ) of the investigatedcarbon steel. The measured and the reference thermal histories, and thetemperature difference between them are recorded. The sensitivity toheat effects of phase transformations in this approach depends on thedistance between the two thermocouples, and further needs repetitiveexperiments to be optimized. In addition, the experiment is difficult tocontrol. The manner of obtaining the reference thermal cycle limits theapplicability of this approach only to solid-state phase transformationsin the HAZ and does not allow investigating the solidification behaviorand the other phase transformations in weld metal.

Dilatometric analysis (DA) is based on measuring the volume changes thataccompany the phase transformations in metallic materials. This methodis mainly applied in combination with devices for simulation of thermaland thermo-mechanical processing, and is capable of determining thesolid-state phase transformations only. Since DA has low sensitivity tosome solid-state phase transformations, it is inapplicable forsolid-liquid phase transformations, and is insensitive to moststructural changes. Dilatometry can be used to evaluate actual thermalcycles and heating and cooling rates associated with those cycles insuch a way as to quantify dimensional changes of the material producedby such changes in temperature. Nevertheless, DA cannot be used in-situ,as it requires special sample types and can only detect phasetransformations where there is a significant change in sample dimension.In addition, it cannot detect structural changes, such asrecrystallization.

Different devices for simulation of thermal and thermo-mechanicalprocessing are available. Such devices are based on resistance,induction, convection or light radiation heating of laboratory scalespecimens. These devices use dilatometric analysis for determining thesolid-state phase transformation temperatures. Because of the controlloops used for controlling the heating and cooling rates, DTA isinapplicable in combination with such devices. Some thermo-mechanicalsimulators are not capable of reproducing the extremely high heating andcooling rates at the high temperature range that are typical for themost welding processes. This results in longer dwell times in austenitephase field (for steels), leading to larger grain size, lowertransformation temperatures and consequently higher content of lowertemperature products of austenite decompositions and higher hardness inthe simulation specimens, compared to the real HAZ. The above techniqueis not capable of simulating the solid-liquid and solid-state phasetransformations. In addition, the simulation equipment is complex inshape and involves expensive laboratory setups.

In another form, weld microstructure simulation equipment based on lightradiation heating has been disclosed. The specimen is heated by focusedhigh-power lamps and the specimen's temperature is controlled by athermocouple. The cooling rate is controlled by the flow rate of astream of shielding gas and simultaneous heating. The HAZ simulationspecimen is a small thin wall tube that is in continuous contact with adilatometer that is used to determine the phase transformationtemperatures. The weld simulation specimen is a small cylinder that isattached to a thermocouple and melts over it forming a small ball. Thesolidification temperature range is determined by differentiation of thethermal history (measured by the thermocouple) using an analogelectronic device. The main disadvantages of this equipment are that ithas difficulty in resembling the actual weld and HAZ heating and coolingrates. In addition, it exhibits non-uniform heating of the HAZsimulation specimen. Moreover, the small volume of the weld simulationspecimen does not allow resembling the actual weld solidificationpatterns.

The available methods and devices have a number of disadvantages thatlimit their usefulness for measuring phase transformations andstructural changes in structural alloys during actual or simulatedprocessing. Thus, what is desired is a method for determining phasetransformation temperatures and structural changes under eithersimulated or actual operating environments for material processing. Whatis also desired is a device for performing more accurate simulations toevaluate material phase transformations and structural changes.

SUMMARY OF THE INVENTION

These desires are met by the present invention, where a device isconfigured for measuring simulated temperatures that are associated withactual material processing conditions, and converting such measuredtemperatures into phase transformation or structural change information.The method of the present invention includes a technique for identifyingphase transformations and structural changes in metals and alloys undereither simulated or actual metal processing conditions. From measuredtemperature values, a thermal history of the metal specimen beingprocessed or evaluated is recorded for the regimes that undergo phasetransformations. From this thermal history, the phase transformationtemperatures can be determined by what the present inventors refer to assingle sensor differential thermal analysis (SSDTA), which differs fromconventional DTA in that rather than relying on the acquisition ofactual reference temperature data with which to compare sensed specimentemperature, the reference temperature is calculated using numericalmodeling or a related algorithm based on temperature measured by thesingle sensor. SSDTA does not mean that only a single temperaturemeasurement sensor be present (as multiple sensors can be used indifferent locations within the same specimen (corresponding, forexample, to the areas of solid, liquid or a solid-liquid state)), butmerely that the device and method does not require the presence of areference sensor with which to compare measured temperature valuesagainst in order to establish phase transformation or related structuralchange information.

The capability of the SSDTA method is valuable for numerous actual andsimulated metal processing applications. In welding-specific examples,it can be used for investigating the solidification range andsolid-state phase transformations under actual welding conditions,constructing CCT diagrams for as-solidified and heat-affected weldmetal. For example, valuable information is provided about the weldmetal microstructure evolution in the typical range of cooling rates forshielded metal arc welding (SMAW). The range of welding conditions whichprovide an optimal combination of microconstituents with respect toweldability and mechanical properties is determined. The SSDTA methodprovides reliable, fast and inexpensive monitoring of phasetransformations under actual welding conditions. This can be beneficialfor the development of welding consumables and welding procedures. Ofcourse, the benefits are not limited to welding, and it will beappreciated by those skilled in the art that other material processingapplications can be used. For example, the SSDTA can also be used fordetermining forging and heat treatment temperatures ranges, the onset ofrecrystallization, and ferromagnetic/paramagnetic transformations (theCurie temperature), among other things.

The present invention can be useful in correlating the solidificationranges of material specimens and their solidification crackingtemperature ranges (SCTRs). The SSDTA method has great potential fordetermining weld solidification cracking susceptibility based on theactual solidification temperature range. It allows the detection ofeutectic phase formation and the determination of such material-specificparameters as the size of the solidification range and thenon-equilibrium liquidus and solidus temperatures that are directlyrelated to solidification cracking susceptibility. Compared toconventional DTA, the SSDTA has equal or similar accuracy, and isfurther applicable in actual processing, as well as in simulation ofnon-equilibrium processing conditions.

Compared to the methods for revealing the thermal effects of phasetransformations over the recorded thermal history (thermal analysis) andthe methods for analog and digital differentiation, the proposed SSDTAmethod allows more precise determination of the phase transformationstart and finish temperatures. In addition, compared to the in-situapplication of the two thermocouple DTA method, the new technique doesnot use a reference thermocouple or related sensor, thus simplifying themeasurement and allowing its application in weld metal and avoidingadditional experiments for determining the optimal distance between thethermocouples in order to optimize the sensitivity. Moreover, it permitscontrolling the sensitivity to the thermal effects of phasetransformations and processing separate parts of the measured thermalhistories, thus increasing the accuracy. Thus, it can be seen that theSSDTA method has tremendous application potential for the reliabledetermination of the solid-liquid and solid-state phase transformationtemperatures and structure changes under the conditions of actual orsimulated welding, casting, heat treatment and other thermal andthermo-mechanical processes.

The SSDTA method is verified by comparison to dilatometric analysisusing a commercially-available thermal simulator. The SSDTA method isalso verified by comparison to conventional DTA usingcommercially-available DTA equipment. The accuracy of the SSDTA methodis confirmed by determining the solidification temperature and the Curietemperature in pure metals. The results of these tests proved that SSDTAhas higher sensitivity to phase transformations than dilatometricanalysis. It was also shown that SSDTA has equal sensitivity andaccuracy with the conventional DTA in determining phase transformationsand structural changes. The SSTDA is applicable in actual and simulatedprocessing conditions, thus providing a superior alternative to theavailable in-situ and simulation techniques that generally use differentvariations of DTA or dilatometric analysis for determining the phasetransformation temperatures.

According to a first aspect of the invention, a method of conductingsingle sensor differential thermal analysis of a material is disclosed.The method includes placing a specimen of the material in thermalcommunication with a heat source, heating the specimen with the heatsource, acquiring data associated with measuring a temperature of thespecimen, calculating reference data, comparing the acquired andreference data, and generating phase transformation temperatures basedon the computed temperature differences. In the present context,calculating reference data may include retrieving the data from astorage location, such as a computer memory, lookup table or the like.

Optionally, the method can be part of a larger metal processingapplication, examples of which include welding, surfacing, hardfacing,brazing, soldering, thermal cutting, casting, heat treatment, forging,rolling, extruding, surface melting and other thermal orthermo-mechanical processing. The method may be for a real processingstep in an actual metal processing environment, or may be a simulationof non-equilibrium solid-liquid and solid-state phase transformations.In the present context, a phase transformation is considered to benon-equilibrium if it does not strictly obey the material's phasediagram which is determined under conditions of thermal and chemicalequilibrium. The method may further include reducing exposure of thetemperature measuring sensor to electromagnetic noise during thetemperature measuring. In one form, reducing exposure can be achieved bygrounding one or more of a data acquisition system and a temperaturemeasuring sensor. In another option, the calculated reference data canbe generated by a known formula, where the temperature information canbe derived exclusively from the temperature data taken from thespecimen. In yet another option, the power output of a simulation devicecan be controlled to closely follow a predetermined thermal historythrough a feedback-based control loop. In addition, the method caninclude compensation in heating and cooling rates caused by the thermaleffects of phase transformations and structural changes. In this way, apredetermined thermal history, while simultaneously recording the poweroutput of the simulation device, can be realized.

According to another aspect of the invention, a device for investigatingphase transformations in a material is disclosed. The device includes achamber defining a substantially enclosed environment, a source ofenergy configured to heat a specimen of the material that is placed inthe chamber, and a mold defining a place where the specimen can beeither placed while being heated, or where the specimen can be collectedin once it has been partially or completely melted. In the presentcontext, the term “substantially” refers to an arrangement of elementsor features that, while in theory would be expected to exhibit exactcorrespondence or behavior, may, in practice embody something slightlyless than exact. As such, the term denotes the degree by which aquantitative value, measurement or other related representation may varyfrom a stated reference without resulting in a change in the basicfunction of the subject matter at issue. In addition, the deviceincludes a hearth that is either disposed in the chamber or forms a part(such as a lower surface) thereof. The hearth is configured to becooperative with the mold such that upon heating of the specimen in thechamber, at least a molten portion of the specimen collects in the mold.In addition, the device includes a data acquisition system that includesa temperature measuring sensor and a computation device. The temperaturemeasuring sensor is placed adjacent the specimen such that it is inthermal communication therewith to sense the temperature of thespecimen, while the computation device (for example, a computer)converts the measured temperature data into phase transformationinformation. Conversion of the measured temperature data is facilitatedby comparing it to reference thermal data such that differential datathat corresponds to specimen phase transformation is produced.

According to yet another aspect of the invention, a device forinvestigating phase transformations in a metallic specimen undersimulated operating conditions is disclosed. The device includes achamber and a source of energy configured to heat the metallic specimen,both as described in conjunction with the previous aspect. In addition,the device includes a mold that collects a molten portion of themetallic specimen therein upon heating of the specimen. The device alsoincludes a hearth disposed in or forming a part of the chamber. Passagesformed in the hearth can be used for controlled atmosphere conduit. Thedevice further includes one or more temperature measuring sensorsdisposed relative to the specimen to sense its temperature.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The following detailed description of the preferred embodiments of thepresent invention can be best understood when read in conjunction withthe following drawings, where like structure is indicated with likereference numerals and in which:

FIG. 1 illustrates a cutaway view of a device for investigating phasetransformations according to an embodiment of the present invention;

FIG. 2 illustrates a cutaway view of a first mold configuration;

FIG. 3 illustrates a cutaway view of a first mold configuration where asingle temperature-measuring device is being used;

FIG. 4 illustrates a cutaway view of an alternate embodiment of thepresent invention;

FIG. 5A represents the measured cooling thermal history and tworeference curves of high strength low alloy steel according to an aspectof the present invention, where the reference curves are generated byoptimizing only the time parameter;

FIG. 5B represents increased sensitivity in determining the phasetransformation heat effects due to the generated reference curve of FIG.5A, where temperature change is presented as a function of thetemperature;

FIG. 5C represents increased sensitivity in determining the phasetransformation heat effects due to the generated reference curve of FIG.5A; where temperature change is presented as a function of time;

FIG. 6A illustrates two measured cooling histories generated during aspecimen processing simulation;

FIG. 6B illustrates the heat release during solidification of thespecimen of FIG. 6A;

FIG. 6C illustrates the heat release during solid state transformationof delta ferrite to austenite of the specimen of FIG. 6A;

FIG. 6D illustrates the beginning of heat release during solid statetransformation of austenite to martensite of the specimen of FIG. 6A;

FIG. 6E illustrates the finishing of heat release during solid statetransformation of austenite to martensite of the specimen of FIG. 6A;

FIG. 7 illustrates the SSDTA method according to an aspect of thepresent invention being conducted on a fusion weld, showing threepossible locations for a temperature measuring sensor, as well as dataacquisition and calculation equipment;

FIG. 8 illustrates the SSDTA method of FIG. 7, further includinggrounding means;

FIG. 9 illustrates a flow chart associated with a single sensordifferential thermal analysis algorithm according to the presentinvention; and

FIG. 10 illustrates a flow chart associated with an intelligent feedbackloop according to the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring first to FIGS. 1 through 3, an embodiment of the device 10according to the present invention includes a chamber 12, a source ofenergy 14, and a hearth 16 (shown with particularity as 16A) on which aspecimen of material 18 is heated. Specimens 18 can exist in a solidstate (i.e., not melted), solid-liquid state (i.e., partially melted) orliquid state (i.e., completely melted). The chamber 12 is made of aheat-resistant material (such as metals and their alloys), and forms ahermetic seal between the hearth 16 and a lid 20. In certain forms, theheat-resistant chamber material may be transparent, such as theaforementioned borosilicate glass. In one form, the chamber 12 forms ahermetic seal between the hearth 16 and lid 20. A controlled atmosphereis maintained in the chamber 12 to protect the specimen 18 from thesurroundings, and may include an inlet 22 and outlet 24. In addition, avacuum 26 can be used to help maintain the controlled atmosphere. Thespecimen 18 weight and shape depending on the application. The source ofenergy 14 may be in one or more numerous forms, and either concentratedor non-concentrated. Examples of the first include an electric arc orplasma arc, plasma, laser or electron beam, while examples of the secondinclude induction heating, convection heating or the like. In theversion shown, the source of energy 14 enters the chamber 12 through thelid 20 and heats the specimen 18, although it will be appreciated bythose skilled in the art that the precise location of the source ofenergy 14 relative to the chamber 12 is not critical.

The hearth 16 is made of a high thermal conductivity or heat resistantmaterial, and may be configured in one of at least two configurations,both of which may include a mold 28. The first configuration hearth 16A,as shown in FIGS. 1 through 3, utilizes one or more replaceable molds 28(shown with particularity as mold 28A) that hold the specimen 18 andfacilitate its heating. The mold 28 is cooled by internal liquid coolingpassages, with one or more cooling liquid inlet passages 32 and one ormore cooling liquid outlet passages 34.

In the second configuration, as shown in FIG. 4, hearth 16B is intendedfor complete melting of the specimen 18. Hearth 16B is equipped with atransfer mechanism 35 by which the molten material 18 is cast into areplaceable mold 28B, positioned below the hearth, FIG. 4. The transfermechanism 35 separates the hearth 16 from the mold 28 in order to meltthe specimen 18 completely in the hearth 16. After the specimen 18 iscompletely melted, the transfer mechanism 35 is opened, thus allowingthe molten metal to flow down into the mold 28. The transfer mechanism35, an example of which can be a gate valve, is disposed between thehearth 16B and the mold 28B to allow transfer of molten metal from thehearth 16B to the mold 28B. In a variation, the molten metal fromspecimen 18 in the hearth 16 is delivered through open hearth with acentral hole. The specimen 18 is melted over the hole and the moltenmetal passes through it and enters the mold 28. The molds 28 for bothhearth designs are made of heat resistant or refractory material and maybe internally liquid cooled as previously discussed. For example, themolds 28A, 28B can be made from a ceramic, a bimetallic or a metalcoated with a ceramic or related refractory. After melting, the specimen18 is transferred into a mold 28B where it solidifies. The hearth 16Bsimulates the conditions of casting and allows the liquid-solid andsolid-state phase transformations to be determined during cooling, andto perform some weldability or castability tests.

The heating and cooling rates of the specimen 18 are controlled bysimultaneously controlling the power regime of energy source 14 and therespective mold cooling capacity. The latter is controlled by thecooling liquid flow rate that passes through the cooling liquid inletand outlet 32, 34, as well as the mold material thermal conductivity andcapacity, and the mold mass and geometry. The high power density andlarge span of cooling capacity of device 10 allow simulation of a widerange of heating and cooling rates, as well as thermal gradients. Thusthe device 10 is capable of reproducing the thermal conditions ofvariety of liquid-solid and solid-state metal processing applicationsincluding welding, surfacing, hardfacing, surface melting, casting, heattreating or the like. In addition, device 10 is capable of simulatingsome fabricability tests (for example, weldability tests, castabilitytests or the like), or some other idealized conditions.

This hearth 16A shown in FIGS. 1 through 3 can be used to simulate theconditions of welding, surfacing and surface melting. In theconfiguration shown in FIG. 1, the specimen 18 is heated by an electricarc in inert atmosphere; in-situations where the specimen 18 is melted,the material of the specimen 18 solidifies over thermocouple 30. Such aconfiguration allows investigation of the liquid-solid and solid-statephase transformations during cooling of the material of specimen 18.Referring with particularity to FIG. 2, the thermocouples 30 arecapacitor discharge welded in holes in mold 28A so that the tips 31would coincide respectively with the molten region 18B and HAZ 18A ofspecimen 18. This option allows investigating the liquid-solid andsolid-state phase transformations during both heating and cooling.Referring with particularity to FIG. 3, the specimen 18 is melted byenergy source 14 and solidifies in a ceramic mold 28A. The use of theceramic mold 28A, with its relatively low thermal conductivity, allowsinvestigating the liquid-solid and solid-state phase transformations atslow cooling rates.

A microprocessor-based system with an intelligent feedback loop can beused to control the energy source 14 power output regime in order torealize a predetermined thermal history at a particular mold 28 coolingcapacity. The intelligent feedback loop includes continuous measuringthe temperature of specimen 18, comparing it to the predeterminedthermal history that may be stored in memory of computation system 38,adjusting the real time energy source 14 power output in order for thespecimen 18 to follow the predetermined thermal history, and recordingthe regime of change of the power controlling parameters.

Existing thermal and thermo-mechanical simulation devices use a controlloop to simulate predetermined thermal histories. This consists ofcontinuous measurement of the temperature of the processed sample andcomparing it to a predetermined thermal history. Their control loops aresensitive enough to compensate (such as by modification of the poweroutput) for any deviations of the simulated thermal history from thepredetermined one. They can also compensate the changes in the heatingand cooling rate caused by the thermal effects of phase transformationsand structural changes, thus making their use for thermal anddifferential thermal analyses inapplicable for measuring phasetransformation temperatures and structural changes, and allowing onlythe less sensitive dilatometric analysis to be applied.

Referring next to FIG. 10, a flow chart showing the application of theintelligent feedback loop to the present invention is shown, where therecorded power output parameters are filtered from any unwanted noiseand from the effects of compensating the phase transformation heateffects. After that, the filtered power output is applied to reproducethe predetermined thermal history on a new specimen 18 of the sameshape, size and material as the first one, without using a control loop.In this way, the intelligent feedback loop allows reproducingpredetermined thermal histories without the device 10 compensating(erasing) the thermal effects of phase transformations and structuralchanges. This way, the SSDTA can be used for determining the phasetransformation temperatures and structural changes with the simulationdevice 10. This approach also allows replacing or paralleling thestandard dilatometric technique in available simulation devices formeasuring phase transformations by the present SSDTA. Stated anotherway, instead of erasing the thermal effects of phase transformations (asis done in existing simulation devices), the intelligent feedback loopdoes not erase the phase changes, thus allowing the SSDTA to be usedwith the present and existing simulation devices.

Referring with particularity to FIG. 10, steps associated with using anintelligent feedback loop according to an aspect of the presentinvention is shown. First, a predetermined thermal history is generated.From there, a simulation of that thermal history and continuousmeasurement of the temperature of a laboratory scale specimen 18 areconducted, after which continuous comparisons are made between themeasured temperature of specimen 18 and the thermal history. Results ofthis can be used to provide continuous control of the power output ofthe source of energy 14, thereby ensuring that the measured temperaturein specimen 18 follows the predetermined thermal history. Thecomputation system 38 (which as mentioned before may be a part of orcooperative with, data acquisition system 36) may be used to acquire,filter and save what is referred to as a power output history. Theintelligent feedback loop can then reproduce the filtered power historyover a new specimen 18. The computation system 38 can further acquireand save a thermal history associated with the new specimen 18 as anacquired thermal history, which can be processed by SSDTA.

The specimen temperature is measured by sensors 30 that can be contactor non-contact. These sensors 30 can be chosen from a variety ofdevices, such as thermocouples, infrared pyrometers, optical fibersensors or other contact or non-contact sensors. The signals from thesensors 30 are recorded by a data acquisition system 36 andmicroprocessor-based computation system 38 (such as a personal computer)as thermal histories. The latter are then processed by SSDTA software 40that is loaded in computation system 38 (in the form of a computer,calculator or other data-manipulating means) in order to revealinformation related to the material, including phase transformationthermal effects and transformation start and finish temperatures.Although shown as three separate components in FIG. 1, it will beappreciated by those skilled in the relevant art that data acquisitionsystem 36, computation system 38 and SSDTA software 40 may be integratedinto a single unit 100, and that either configuration is equallyapplicable to the present invention. Furthermore, the temperaturemeasuring sensors 30 may also form an integral part of the dataacquisition system 36.

FIGS. 5A through 5C show an example of SSDTA according to an aspect ofthe present invention. Referring first to FIG. 5A, the measured coolingthermal history (Tm) and two reference curves (Tr) at two differenttimes, 6.3 and 6.7 seconds are shown. These reference curves aregenerated by optimizing only the parameter Δt in the analytical formuladiscussed below. Generating a reference curve that is closer to themeasured thermal history increases the sensitivity in determining thephase transformations heat effects. This can be seen in FIGS. 5B and 5C,where by reducing the Δt, which reduces the instant values of ΔT in FIG.5A, results in bigger deviations of ΔT on the T(ΔT) of FIG. 5B, andΔT(t) of FIG. 5C. FIGS. 5B and 5C also represent the effect of digitalfiltering of some recorded electromagnetic noise by applying the methodof running average, where k7 represents a filtering coefficient of thenumber of consecutively averaged datapoints (in this case, 7). Thissignificantly reduced the noise and made the heat effects of phasetransformations more clearly determinable. The actual phasetransformation temperatures on FIGS. 5B and 5C are determined by thesudden change of the rate at which ΔT decreases as a function of thetemperature (T) or the time (t).

Referring next to FIGS. 6A through 6E, a typical thermal historyobtained with the device and method of the present invention is shown,where the thermal effects of phase transformations are revealed by theSSDTA software 40. In this case, the specimen was a stainless steel(12Cr-6.5Ni-2.5Mo), where the maximum temperature was 1539 degreesCelsius, and the cooling time between 800 degrees Celsius and 500degrees Celsius (Δt_(8/5)) was 16.9 seconds. Referring first to FIG. 6A,two measured thermal histories are shown, with the temperature (indegrees Celsius) along the ordinate shown against the time (in seconds)along the abscissa. Referring next to FIG. 6B, the heat release duringsolidification as delta ferrite is shown. This is a result of the SSDTAsoftware 40 processing the measured cooling history by generating alocal reference curve. The determined liquidus and solidus temperaturesare shown on this curve as points L and S. Referring next to FIG. 6C,the heat release during solid state transformation of delta ferrite toaustenite is shown. As with FIG. 6B, this results from the processing bythe SSDTA software 40 of the measured cooling history by SSDTAgenerating a local reference curve. The determined transformationstarting and finishing temperatures on this curve are shown as pointsA_(S) and A_(F). Referring next to FIG. 6D, the beginning of heatrelease during solid state transformation of austenite to martensite isshown. As before, this is a result of processing the measured coolinghistory by generating a local reference curve. Because in this case thethermal effect is large, separate local references curves are used todetermine the transformation starting and finishing temperatures. Thedetermined transformation starting temperature on this curve is shown asM_(S). Referring next to FIG. 6E, the finishing of heat release duringsolid state transformation of austenite to martensite is shown, which isalso derived from processing the measured cooling history by generatinga local reference curve. Because in this case the thermal effect islarge, separate local references curves are used to determine thetransformation starting and finishing temperatures. The determinedtransformation finishing temperature is shown as point M_(F) on thiscurve.

Referring next to FIG. 7, an application of the SSDTA method to a fusionwelding situation is shown. As with the device 10 of FIGS. 1 through 4,the temperature measurements are performed by thermocouples 30 that arecapacitor discharge welded into holes formed in the base metal 150 sothat the thermocouples tips 31 would coincide with the HAZ 160 or weldmetal 170. Manual plunging of thermocouples 30 into the molten pool canalso be conducted. The signal from thermocouple 30 is digitally acquiredby digital acquisition system 36 and computation system 38 as a measuredthermal history, which is then opened by SSDTA software 40. Thissoftware 40 calculates a preliminary reference thermal cycle by wellknown analytical formulae using the parameters of the measured thermalhistory, including initial (preheat) temperature (T₀), maximumtemperature (T_(P)), and cooling time between eight hundred and fivehundred degrees Celsius (Δt):

$\begin{matrix}{T = {T_{0} + {{\theta_{k}\left( \frac{\Delta\; t}{t} \right)}^{\frac{1}{k}}\exp} - \left\lbrack \frac{\theta_{k}^{k}\Delta\; t}{{{ket}\left( {T_{P} - T_{0}} \right)}^{k}} \right\rbrack}} & (1)\end{matrix}$

where:

$\begin{matrix}{\frac{1}{\theta_{k}^{k}} = {\left( {\frac{1}{\left( {500 - T_{0}} \right)^{k}} - \frac{1}{\left( {800 - T_{0}} \right)^{k}}} \right).}} & (2)\end{matrix}$In the above, θ is an expression used for simplification of the way theprevious formula is presented, while k is related to heat extractioncapacity of the processed object. The preliminary reference cycle isthen subjected to optimization by the least square method or othermethods, varying the above mentioned parameters and by shifting it alongthe temperature and time axis. In this particular case, the optimizationis done for the cooling part of the thermal history and generates aconstantly decreasing function ΔT(t) with a predetermined rate,typically three to five degrees Celsius per each one hundred degreeCelsius cooling increment. The obtained solution is presented as twodiagrams: T_(M)(ΔT), as shown in FIG. 5B, and ΔT(t), as shown in FIG.5C. The SSDTA software 40 allows further optimization of the solution bymanually changing the parameters of the calculated reference cycle. FIG.5A presents an example of optimization of the calculated thermalhistory. In this case, the position of T_(R)(t) towards T_(M)(t) isoptimized by changing Δt_(8/5); increasing Δt_(8/5) shifts T_(R)(t)closer to T_(M)(t) thus reducing ΔT(t) and increasing sensitivity to thethermal effects of bainitic and martensitic transformations, as shown inFIGS. 5B and 5C.

Referring next to FIG. 8, again in situations where the temperaturemeasuring sensors 30 are thermocouples, an approach for grounding thethermocouples is used to sense and process temperature signals. In atypical temperature-measuring approach, thermocouples generate a lowlevel voltage signal that can be interfered with by strongelectromagnetic fields generated by external devices, such as electricpower sources or electric power lines. Approaches are needed to reducethe electromagnetic noise in thermocouples and related sensors.

Conventional approaches to reducing the electromagnetic noise inthermocouples and related sensors employ twisted and shielded extensionwires, and in the case of a metal sheathed thermocouple, grounding ameasuring instrument (typically, a data acquisition system) to thethermocouple sheath through the extension wire shield. In one form, thedirect grounding of the measuring instrument is through a connection ata random location on the specimen. In situations involving the passageof electric current through the specimen (for example, during a typicalmetal processing application), the relative locations of thethermocouple, the measurement ground, the power application, and thepower source ground may affect the accuracy of thermocouplemeasurements. In situations involving a liquid metal in a mold made ofelectric insulating material (such as ceramic), such a groundingapproach would be inapplicable, as the data acquisition system should begrounded to the metal (in this case, molten metal), which thethermocouple is in contact with, and as close to the thermocouple aspossible. In situations involving liquid metal in a mold made ofelectric conductive material (such as metal), such an approach(grounding to the mold, for example) would be ineffective because of theunstable electrical contact between the mold and the metal, whichresults from surface oxidation and shrinkage of the molten metal duringits solidification and solid state cooling.

In the SSDTA method of the present invention, the thermocouples 30 areexposed, which places them in direct contact with the specimen 18 underinvestigation. Such contact provides a direct electrical path, therebymaking the conventional grounding approaches incompatible with thepresent invention. In the embodiment shown, there are three temperaturesensing devices (in the form of thermocouples 30A, 30B and 30C). Eachwork independently of the others, and may be used singly or in anycombination to effect the desired temperature measuring. In the presentinvention, the thermocouples 30 generate a low level signal in the rangebetween −8 millivolts and +80 millivolts. The interference discussedabove can compromise the accuracy of thermocouple 30 temperaturemeasurement and, in the most severe cases, make such measurementimpossible. The SSDTA method of the present invention is based on theevaluation of local thermal effects available in the overall thermalhistory of a material specimen subjected to thermal or thermo-mechanicalprocessing. Thus, a significant reduction or complete elimination of theelectromagnetic noise in thermocouple measurements is helpful inestablishing reliable and accurate application of the SSDTA method wherethermocouples 30 are used as the temperature measuring sensors. Thegrounding approach shown in FIG. 8 is useful in-situations involvingdirect contact of the thermocouple 30 with the specimen 18 Grounding themeasuring instrument (i.e., the data acquisition system 36) to thespecimen 18 in a position close to the thermocouple 30 makes the dataacquisition system 36 more insensitive to the electromagnetic noisegenerated in the processed metallic specimen and to the changingelectric paths in it. The data acquisition system 36 is grounded to thespecimen (shown as a weld metal 170) through a grounding wire 130 thatis made of the same type of wire as that of the thermocouple 30 and isgrounded in a close location to the thermocouple tip 31. The groundingwire 130 is connected to the data acquisition system 36 through anextension wire shield 32. Thus, the thermocouple 30 is in contact withthe specimen 18 so that it can measure the specimen 18 temperature,while the data acquisition system 36 (i.e., the measuring instrument) isgrounded to the specimen 18 close to the thermocouple 30. In situationscalling for measuring the temperature of a solid metal specimen 18, boththe ground wire 130 and the thermocouple tip 31 are capacitor dischargewelded to the specimen 18 with a spacing of approximately 1 mm betweenthem, as shown in the figure.

In situations involving the measurement of liquid metal temperature(i.e., that corresponding to the melted state or welding pool of weldmetal 170), both the thermocouple 30B and the ground wire 130 are heldby a ceramic insulator 180 at a spacing of approximately 1 millimeterbetween them. The thermocouple 30B and the ground wire 130 are broughtinto simultaneous contact with the metal by inserting their tips intoliquid metal 170 (as shown in the figure), or by pouring liquid metalover them.

The temperature in a particular area of interest in a specimen 18subjected to processing by fusion or solid state welding, casting, heattreatment, or other thermal or thermo-mechanical application is measuredby a single contact or non-contact temperature sensor 30. The signal ofthe temperature sensor, which is typically analog, is conditioned(usually amplified and sometimes filtered), converted into digital form,then converted to a corresponding temperature signal and recorded intothe operating memory of a computation system 38, where a predeterminedsampling rate can be used. The signal processing can be performed byeither a custom-designed or commercially available data acquisitionsystem 36. Likewise, an algorithm (as discussed below in conjunctionwith FIG. 9) can be utilized, and may be in a form known to thoseskilled in the art, such as software that can be loaded into memory ofcomputation system 38.

The measured thermal history carries information about the heat effectsassociated with the phase transformations of specimen 18. Thesolid-solid and solid-liquid phase transformations and structuralchanges that occur during heating consume or release heat, which resultsin changes of the heating rate inside the temperature range of theparticular transformation. Similarly, the phase transformations andstructural changes during cooling release or consume heat, which resultsin changes of the cooling rate in the respective temperature ranges oftransformation. In the conditions of steep thermal gradients and highheating and cooling rates, which are typical for most of the materialprocessing technologies, these thermal effects are quite small andbarely discernible over the recorded thermal history. The device 10 andaccompanying SSDTA method are configured to reveal this data, whichutilizes only one recorded thermal history, in comparison to traditionalDTA (which utilizes two thermocouples measuring the thermal history of areference specimen with no phase transformations). The approach of thetraditional method is replaced in the present invention by a calculatedreference thermal cycle derived from analytical formulae or numericalmodeling, an example of which follows.

The temperature difference ΔT(t) between the measured thermal history(T_(M)(t)) and the calculated reference thermal cycle (T_(R)(t)) isplotted as function of the time according to the following equation:ΔT(t)=T _(M)(t)−T _(R)(t)  (1)

Then based on T_(M)(t) and ΔT(t) the dependence T_(M)(ΔT) is plotted.The thermal effects of the phase transformations, which are present withthe measured thermal history, cause local changes of ΔT over theT_(M)(ΔT) and ΔT(t) curves, whose beginnings and ends coincide with thestarting and finishing temperatures of the phase transformations, asshown in FIGS. 5A through 5C.

The sensitivity to the thermal effects of phase transformations, andrespectively the accuracy in determining the transformation start andfinish temperatures, strongly depend on the ratio between the currentvalue of ΔT and the magnitude of its change due to the thermal effect oftransformation, FIGS. 5A through 5C. Revealing smaller thermal effectsrequires smaller temperature differences between T_(M)(t) and T_(R)(t).The phase transformations and structural changes during heating andcooling cause local increasing or decreasing in ΔT(t). Consequently,slightly increasing the general trend of ΔT(t) in the case of its localdecreasing and slightly decreasing general trend ΔT(t) in the case ofits local increasing will facilitate sharper detection of thetransformation starting and finishing temperatures.

The device 10 and SSDTA method achieves optimal sensitivity to the heateffect of a particular phase transformation. This is done by optimizingthe calculated reference thermal cycle towards the recorded thermalhistory in order to obtain predetermined values and trend of change inΔT(t) in a particular temperature range.

Referring next to FIG. 9, a flow chart depicting how an algorithm forconducting the SSDTA of the present invention is shown. The first stepincludes browsing folders and selecting one or several files acquired bythe data acquisition system 36, then reading and loading simultaneouslythe selected files. In the next step, the data is filtered. Thisincludes detecting recorded high or low frequency noise, filtering ofthe recorded noise by running average, available digital filters orother filtering procedures, then saving the filtered data (such as tomemory). In a next step, the data is downsized. This includes averagingthe recorded temperature data to a predetermined number of data pointsper incremental temperature (such as degrees Celsius), then generatingand saving the new (downsized) data with a predetermined number of datapoints per the temperature increment. In a next step, data parametersare calculated. This includes determining the initial and maximaltemperatures (T₀ and T_(MAX)), then calculating heating and coolingrates and heating and cooling times in selected temperature ranges, thencalculating dwell times above selected temperatures, in addition todetermination of inflection points, and then saving these parameters inthe files of the filtered or downsized data. In a next step, globalreference curves are generated separately for both the entire heatingpart and the entire cooling part of the data.

The reference curves may be generated by available analytical formula,by available procedures for generation of fitting curves, or bynumerical modeling of heat transfer in the particular conditions ofthermal/thermo-mechanical processing or simulation of processing. Inanother step, the reference curves are optimized. This includesestablishing optimization criteria for best fit with the data,optimizing the parameters of the reference curves by availableoptimization procedures (examples of which may include the least squaremethod, the “steepest slope” method, the Levenberg-Marquardt method, orthe like). In this optimization, the data inflection points can be usedas reference points. In the next step, ΔT(T) and ΔT(t) diagrams can begenerated, where the functions ΔT(T) and ΔT(t) are calculated usingΔT=T_(M)−T_(R) (T_(M) is the measured temperature at each data point andT_(R) is the corresponding temperature of the optimized referencecurve). These generated diagrams can then be saved in a single filetogether with the parameters of optimization. After that, phasetransformation temperatures can be determined. This can be by manualdetermination of the phase transformations starting and finishingpoints, followed by automatic determination of the temperatures and timeat these points. The criteria and procedure for fully automaticdetermining of the phase transformations temperatures can also beapplied, after which these diagrams can be saved and printed or pastedin other files. In a next step, local reference curves can be generatedin a manner generally similar to that of the step involving generationof global reference curves. In addition, this allows generation of localreference curves for each temperature range where phase transformationsare expected to occur, as well as where phase transformations aredetected in accordance with the previous step. Then, the generation ofΔT(T) and ΔT(t) diagrams and the determination of the phasetransformation temperatures of the previous two steps can be repeated.In the next step, the results can be saved and printed. First, save allfinal solutions in separate file folders containing optimized parametersof the reference curves, ΔT(T) and ΔT(t) diagrams as well as phasetransformation temperatures. After that, the results can be printed as aseparate report or pasted into a word processing document.

Having described the invention in detail and by reference to preferredembodiments thereof, it will be apparent that modifications andvariations are possible without departing from the scope of theinvention defined in the appended claims. More specifically, althoughsome aspects of the present invention are identified herein as preferredor particularly advantageous, it is contemplated that the presentinvention is not necessarily limited to these preferred aspects of theinvention.

1. A device for conducting single sensor differential thermal analysisin a material, said device comprising: a chamber defining asubstantially enclosed environment; a source of energy configured toheat a specimen of said material; a mold defining a specimen containingportion therein; a hearth disposed in or forming a part of said chamber,said hearth cooperative with said mold such that upon heating of saidspecimen in said chamber, said specimen collects in said mold; and adata acquisition system configured to measure temperature dataassociated with said specimen, said data acquisition system furtherconfigured to manipulate said data to determine phase transformationinformation associated with said heating, said data acquisition systemcomprising: a single temperature measuring sensor placed in thermalcommunication with said specimen; and a computation device configured toconvert data measured by said single temperature measuring sensor intosaid phase transformation information through comparison of said data toa reference thermal history.
 2. The device of claim 1, wherein saidreference thermal history comprises temperature information that isderived from said measured temperatures taken from said singletemperature measuring sensor.
 3. The device of claim 1, wherein saidsingle temperature measuring sensor is disposed substantially in saidmold.
 4. The device of claim 3, wherein said single temperaturemeasuring sensor comprises a thermocouple.
 5. The device of claim 1,wherein said mold is removably coupled to said hearth.
 6. The device ofclaim 5, wherein said mold is disposed beneath said hearth.
 7. Thedevice of claim 1, wherein at least one of said hearth or said chambercomprises a controlled atmosphere conduit configured to adjust gas flowin said chamber.
 8. The device of claim 7, wherein said controlledatmosphere conduit comprises an chamber inlet passageway and a chamberoutlet passageway.
 9. The device of claim 8, wherein both saidpassageways are formed in said hearth.
 10. The device of claim 7,wherein said controlled atmosphere conduit further comprises a vacuumconduit configured to be coupled to a vacuum source.
 11. The device ofclaim 1, further comprising cooling fluid conduit disposed in said mold.12. The device of claim 1, wherein said mold comprises a high thermalconductivity material.
 13. The device of claim 12, wherein said highthermal conductivity material comprises copper or an alloy thereof. 14.The device of claim 1, wherein said mold comprises a low thermalconductivity material.
 15. The device of claim 14, wherein said lowthermal conductivity material comprises a ceramic or a ceramic-coatedmetal.
 16. The device of claim 1, wherein said data acquisition systemfurther comprises a differential thermal analysis algorithm operatingtherein such that upon operation of said algorithm, said sensedtemperature signals and said reference thermal history are compared togenerate temperature differences that are in turn used to determinephase transformation temperatures for said specimen.
 17. The device ofclaim 1, wherein said source of energy is selected from the groupconsisting of electric arc, plasma arc, plasma, laser, electron beam,inductive heating and conductive heating.
 18. The device of claim 1,further comprising a transfer mechanism disposed between said hearth andsaid mold.
 19. A device for investigating phase transformations in ametallic specimen under simulated operating conditions, said devicecomprising: a chamber defining a substantially enclosed environment; asource of energy configured to heat said metallic specimen; a moldconfigured such that upon heating of said specimen, a portion thereofcollects in said mold; a single temperature measuring sensor disposedrelative to said specimen to sense a temperature thereof; and acomputing means configured to compare temperature data retrieved fromsaid single temperature measuring sensor with a reference thermalhistory of said specimen in order to determine phase transformationinformation of said specimen, wherein said reference thermal history isknown without the need for measuring a reference specimen temperature.20. The device of claim 19, wherein said computing means furthercomprises an intelligent feedback loop.